"A guide to best practices" matching MCP servers:

Provides access to clean code guide documents and enables code quality inspection of external project files based on coding standards and best practices.

Provides Python and FastAPI coding best practices with searchable guidelines, code review capabilities, and actionable improvement suggestions with examples across general coding, performance, and code quality categories.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

Provides professional C++ code style checking, best practices analysis, and modern C++ upgrade suggestions with tools for naming conventions, memory safety, const correctness, and access to comprehensive C++ style documentation.

Reviews MCP servers for quality, security, and best practices, providing scores and improvement plans.

Exposes your organization's Terraform style guide to AI coding agents, enabling them to generate, validate, and ensure Infrastructure as Code follows your specific conventions, naming standards, security defaults, and best practices.

An MCP server that enforces unit testing standards by linting code and guiding agentic coding tools (like Gemini CLI or Claude Code) to follow best practices in test-driven development.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Provides intelligent assistance for Azure Terraform development, including documentation retrieval, code validation, security scanning, and best practices guidance.

Enables local code inspection and analysis for clean code practices, best practices, and actionable recommendations without external API calls or modifying the code.

Provides Flutter best practices, code analysis, and state management recommendations for senior developers.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

A local-first MCP server that scores your codebase's Build Readiness by reading code and running tests on your machine, outputting a diligence-grade score and risk register without uploading your source.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

Classifies SAP ABAP objects against SAP's official Clean Core release catalog to determine API release status and guide S/4HANA implementation.

Enables AI-assisted X++ development for Dynamics 365 Finance and Operations by pre-indexing the entire codebase and providing 54 specialized tools for metadata lookup, code generation, and best practice validation.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

A server providing programming guidelines and coding standards for multiple languages, enabling access and search of best practices for C#, Go, JavaScript, Python, and TypeScript.